CN-121995890-A - Panoramic monitoring and intelligent operation and maintenance system based on digital twinning

CN121995890ACN 121995890 ACN121995890 ACN 121995890ACN-121995890-A

Abstract

The invention discloses a panoramic monitoring and intelligent operation and maintenance system based on digital twinning, and mainly relates to the technical field of digital twinning. Comprises a physical layer for interacting with a physical entity; the digital twin layer is used for constructing and running a dynamic twin model and comprises a data acquisition and fusion module, a three-dimensional model construction and driving module and a model updating and optimizing module; and the intelligent application layer for panoramic monitoring and intelligent decision-making comprises a panoramic visual monitoring module, an intelligent operation and maintenance analysis module and a decision support and cooperative control module. The method has the advantages that the method utilizes the health evaluation model and the performance degradation prediction algorithm fused with the multi-source data to realize accurate prediction and intelligent diagnosis of the equipment state, and forms closed loop optimization from perception, analysis to decision and execution through the self-optimization and cooperative control mechanism of the model, thereby remarkably improving the initiative, the accuracy and the intelligent level of operation and maintenance management.

Inventors

ZHONG RUIYAN
PENG HUI
ZHAO JINE
FANG KUN
LIN YU
XING XUEFENG
FENG ZHIQIANG
KONG XIANGBIN
ZHANG SHAORU
ZHANG QINGPING

Assignees

云鼎科技股份有限公司
山东能源集团景泰盛鲁新能源有限公司

Dates

Publication Date: 20260508
Application Date: 20260226

Claims (9)

1. A panoramic monitoring and intelligent operation and maintenance system based on digital twinning is characterized by comprising: The physical layer is used for carrying out data interaction with a physical entity; The digital twin layer is used for constructing and running a digital mirror image model of a physical entity, is in communication connection with the physical layer, receives real-time data and drives the digital mirror image model to run synchronously; The intelligent application layer is used for carrying out panoramic visual monitoring and intelligent analysis decision based on the state of the digital mirror image model, and is in communication connection with the digital twin layer; The digital twin layer includes: the data acquisition and fusion module is used for acquiring multi-source heterogeneous real-time operation data and environment data from the physical layer; The three-dimensional model construction and driving module is used for constructing a high-fidelity digital model according to geometric, physical and behavioral rules of a physical entity and driving the digital model to realize virtual-real synchronization by utilizing the data processed by the data acquisition and fusion module; The model updating and optimizing module is used for dynamically correcting and improving the precision of the digital model according to the state change of the physical layer and the analysis feedback of the intelligent application layer; the intelligent application layer comprises: The panoramic visualization monitoring module is used for carrying out integrated rendering and multidimensional display on the digital mirror image model and the associated real-time data and alarm information thereof; The intelligent operation and maintenance analysis module is used for carrying out operation trend prediction, abnormality diagnosis and health degree assessment through a preset algorithm model based on the real-time and historical state data of the digital mirror image model; and the decision support and cooperative control module is used for generating an operation and maintenance strategy suggestion or sending a control instruction to the physical layer according to the output result of the intelligent operation and maintenance analysis module.
2. The digital twinning-based panoramic monitoring and intelligent operation and maintenance system of claim 1, wherein said data acquisition and fusion module performs the steps of: s11, acquiring multi-source heterogeneous original data including vibration, temperature, pressure, current, video stream and equipment log through a sensor network, monitoring equipment and an existing service system which are deployed in a physical entity; step S12, preprocessing operation comprising data cleaning, format standardization, time stamp alignment and missing value processing is carried out on the multi-source heterogeneous original data; step S13, adopting a data fusion algorithm based on Kalman filtering or extended Kalman filtering to fuse data describing the same object or the same state from different sources, and generating unified state description information with higher precision and reliability; The preprocessed and fused data are synchronously stored in a real-time database and a historical database, and a driving data source is provided for the three-dimensional model construction and driving module.
3. The digital twinning-based panoramic monitoring and intelligent operation and maintenance system according to claim 1, wherein the three-dimensional model building and driving module performs the following procedures: s21, constructing a three-dimensional geometric model comprising geometric shapes, internal structures and spatial relations based on a computer aided design drawing, a building information model or three-dimensional scanning point cloud data of a physical entity; s22, forming a mechanism model with physical properties and behavior simulation capability by adding material properties, motion constraint, physical rules and behavior logic on the basis of the three-dimensional geometric model; Step S23, establishing a dynamic mapping relation between each parameter of the mechanism model and the unified state description information output by the data acquisition and fusion module; And step S24, mapping the state change of the physical entity to the corresponding parameter of the mechanism model according to the dynamic mapping relation, and driving the mechanism model to perform synchronous simulation operation so as to realize the dynamic consistency of the digital virtual body and the physical entity.
4. The digital twinning-based panoramic monitoring and intelligent operation and maintenance system according to claim 1, wherein when the intelligent operation and maintenance analysis module performs the equipment health assessment, the following health index calculation model is adopted: ; Wherein, the Expressed in time The comprehensive health index of the equipment at the moment has the value range of The larger the value, the better the health status; 、、 is a weight coefficient and satisfies The contribution weights of real-time operation parameters, performance degradation trends and abnormal events to the overall health degree are respectively represented; Represent the first The key operation parameters are in time Is obtained by linear or nonlinear mapping based on a reference range of the parameter in a healthy state, such that ; Represent the first The weights of the individual critical operating parameters are, ; Is the first The key operation parameters are used for further calibration under ideal health conditions; Representing performance degradation indexes obtained through trend prediction algorithm based on equipment operation history data, wherein the value range is 1 Represents no degradation, 0 represents complete degradation; Expressed in time A weighted sum of the severity of the diagnostically confirmed abnormal events occurring within a predetermined time window, the weighted sum having a value range of 0 Indicates no abnormality, 1 indicates the occurrence of the most serious abnormality; the intelligent operation and maintenance analysis module obtains according to calculation And the value is used for dividing the health state of the equipment into a plurality of grades and carrying out visual identification in the panoramic visual monitoring module.
5. The digital twinning-based panoramic monitoring and wisdom operation and maintenance system according to claim 4, wherein the performance degradation indicator is Obtained by the following steps: extracting a long-term operation parameter time sequence of the equipment in a healthy state from a historical database as a training data set; Learning the training data set by adopting an autoregressive integral moving average model or a long-term and short-term memory neural network, and establishing a parameter prediction model under the normal running state of the equipment; inputting actual operation parameters in a historical window before the current moment into the parameter prediction model to obtain predicted values of all parameters at the current moment; Calculating residual errors between actual values and predicted values of the key operation parameters at the current moment, and carrying out standardization processing on the residual errors; Inputting the standardized residual vector into a pre-trained single-class support vector machine model, and calculating to obtain the deviation degree score between the current state and the normal state mode; passing the degree of deviation score through Mapping of functions to The interval, the mapped result is the performance degradation index The closer the value is to 0, the more severe the degradation.
6. The digital twinning-based panoramic monitoring and intelligent operation and maintenance system of claim 1, wherein the panoramic visualization monitoring module performs the following process: Integrating the dynamic digital mirror image model output by the three-dimensional model construction and driving module, measuring point data in a real-time database, video monitoring flow and alarming and evaluating results from the intelligent operation and maintenance analysis module; Providing various interactive visual functions including three-dimensional scene free navigation, equipment structure explosion view, data panel dynamic mounting, historical state backtracking and virtual tour inspection path planning; a light-weight rendering engine based on WebGL is adopted to realize smooth display and interaction of a large-scale complex three-dimensional scene and massive real-time data through a Web browser; according to the roles and the authorities of the users, the monitoring information with different levels and different dimensions is customized and displayed, and the data drilling and analysis of key indexes are supported.
7. The digital twinning-based panoramic monitoring and intelligent operation and maintenance system of claim 1, wherein said model update and optimization module performs the following process: step S31, continuously monitoring errors between key simulation output of the digital mirror image model and actual monitoring data of a corresponding physical entity; Step S32, when the error exceeds a preset threshold, triggering a model parameter self-correction flow, and adjusting specific parameters in the mechanism model by adopting an optimization algorithm based on gradient descent or Bayesian inference so as to reduce simulation error; Step S33, receiving a new mode or association rule which is found by the intelligent operation and maintenance analysis module in anomaly diagnosis or prediction analysis and is not fully described by the existing model; And step S34, converting the new mode or association rule into a model constraint or supplementary rule, and carrying out incremental updating and knowledge fusion on a behavior logic library of the digital mirror image model to improve the representation and prediction capability of the model on complex working conditions and unknown states.
8. The digital twinning-based panoramic monitoring and wisdom operation and maintenance system according to claim 1, wherein the decision support and co-control module performs the following process: S41, receiving equipment health assessment, fault early warning and residual service life prediction information output by the intelligent operation and maintenance analysis module; Step S42, generating a targeted maintenance strategy suggestion based on a preset operation and maintenance knowledge base and a rule engine in a matching way, wherein the suggestion comprises a maintenance type, a suggestion time, required resources and operation steps; Step S43, for the scene of emergency fault or need immediate intervention, after authorized confirmation, automatically generating a control instruction sequence, and issuing the control instruction sequence to a corresponding actuator or control system through the physical layer to realize quick response and closed-loop control; And S44, recording the execution process and the result of all the decision suggestions, and feeding back the execution effect to the model updating and optimizing module and the intelligent operation and maintenance analyzing module for optimizing the subsequent analysis and decision.
9. The digital twinning-based panoramic monitoring and wisdom operation and maintenance system according to claim 1, wherein the physical layer further comprises edge computing nodes disposed on a network edge side near a physical entity for: carrying out localized preprocessing and filtering on the original data acquired by the sensor network, and reducing the data volume and bandwidth pressure transmitted to a cloud or central server; running a lightweight anomaly detection and diagnosis algorithm, and analyzing local data in real time to realize millisecond-level to second-level rapid anomaly identification and local alarm; and when the network is interrupted or communication with an upper layer system is not smooth, local safety interlocking control or basic operation and maintenance operation is executed according to a preset strategy, so that the basic safety and operation of physical entities are ensured.

Description

Panoramic monitoring and intelligent operation and maintenance system based on digital twinning Technical Field The invention relates to the technical field of digital twinning, in particular to a panoramic monitoring and intelligent operation and maintenance system based on digital twinning. Background With the rapid development of internet of things, big data and artificial intelligence technology, operation and maintenance management of industrial equipment, infrastructure and large parks is advancing towards digitization and intelligence. Conventional monitoring and operation systems typically rely on discrete deployed sensors, independent monitoring screens (e.g., video monitoring), and a simple threshold-based alert mechanism. The system can provide basic operation data acquisition and abnormality alarm functions, but has increasingly prominent limitations that firstly, each subsystem is isolated in data, lacks effective fusion and association analysis, is difficult to grasp the overall operation state from the global view, secondly, a monitoring mode is mainly based on a two-dimensional chart and an isolated video picture, information presentation is not visual, the expressive force on the internal state and the spatial relation of complex equipment is insufficient, and finally, operation and maintenance decisions are dependent on manual experience, response lag and lack of predictive analysis capability on equipment performance degradation and potential faults, and the system belongs to 'passive response' operation and maintenance. In recent years, digital twin technology has received attention as a key enabling technology for achieving deep fusion of the physical world and the information space. The method provides a new idea for monitoring and operation and maintenance by constructing a high-fidelity virtual model of a physical entity and utilizing real-time data to drive and synchronize. However, the digital twin is still applied to the practice of panoramic monitoring and intelligent operation and maintenance, so that on one hand, the existing digital twin model is often focused on geometric appearance and static data display, dynamic coupling depth of the model and real-time data is insufficient, real-time performance and accuracy of virtual-real synchronization are to be improved, on the other hand, integration level of the twin model and a background intelligent analysis algorithm (such as health assessment and fault prediction) is not high, an iteration mechanism of model update is not sound, and analysis decision-making capability based on the twin model is limited, and potential of the digital twin in simulation, prediction and optimization cannot be fully exerted. Therefore, how to construct a system integrating high-fidelity dynamic twinning, multi-source data depth fusion, panoramic visual monitoring, and depth intelligent analysis and decision-making into a whole, and realize the transition from 'passive monitoring' to 'active prediction and intelligent operation and maintenance', has become a technical problem to be solved in the art. Disclosure of Invention The invention aims to provide a panoramic monitoring and intelligent operation and maintenance system based on digital twinning, which forms closed-loop optimization from perception, analysis to decision and execution through a self-optimization and cooperative control mechanism of a model, and remarkably improves the initiative, the accuracy and the intelligent level of operation and maintenance management. The invention aims to achieve the aim, and the aim is achieved by the following technical scheme: the invention provides a digital twinning-based panoramic monitoring and intelligent operation and maintenance system, which comprises: The physical layer is used for carrying out data interaction with a physical entity; The digital twin layer is used for constructing and running a digital mirror image model of a physical entity, is in communication connection with the physical layer, receives real-time data and drives the digital mirror image model to run synchronously; The intelligent application layer is used for carrying out panoramic visual monitoring and intelligent analysis decision based on the state of the digital mirror image model, and is in communication connection with the digital twin layer; The digital twin layer includes: the data acquisition and fusion module is used for acquiring multi-source heterogeneous real-time operation data and environment data from the physical layer; The three-dimensional model construction and driving module is used for constructing a high-fidelity digital model according to geometric, physical and behavioral rules of a physical entity and driving the digital model to realize virtual-real synchronization by utilizing the data processed by the data acquisition and fusion module; The model updating and optimizing module is used for dynamically correcting and improving the precision of the